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ISSN:2164-6376 (print)
ISSN:2164-6414 (online)
Discontinuity, Nonlinearity, and Complexity

Dimitry Volchenkov (editor), Dumitru Baleanu (editor)

Dimitry Volchenkov(editor)

Mathematics & Statistics, Texas Tech University, 1108 Memorial Circle, Lubbock, TX 79409, USA

Email: dr.volchenkov@gmail.com

Dumitru Baleanu (editor)

Cankaya University, Ankara, Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania

Email: dumitru.baleanu@gmail.com

Solution of Non-Linear Chemical Processes using Novel Differential Gradient Evolution Algorithm

Discontinuity, Nonlinearity, and Complexity 11(1) (2022) 161--181 | DOI:10.5890/DNC.2022.03.014

Muhammad Farhan Tabassum$^{1}$, Nazir Ahmad Chaudhry$^{2}$, Ali Akg "{u}l$^{3}$ , Muhammad Farman$^{4}$, Sana Akram$^{1}$

$^{1}$ Department of Mathematics, University of Management and Technology, Lahore, 54000, Pakistan

$^{2}$ Department of Mathematics, Faculty of Engineering, Lahore Leads University, Lahore, Pakistan

$^{3}$ Department of Mathematics, Art and Science Faculty, Siirt University, 56100 Siirt, Turkey

$^{4}$ Department of Mathematics and Statistics, University of Lahore, Lahore, 54000, Pakistan

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Abstract

Optimization for all disciplines is very important and relevant. Optimization has played a key role in the design and operation of industrial reactors, separation processes, heat exchangers and complete plants in Chemical Engineering. In this paper, a novel hybrid meta-heuristic optimization algorithm which is based on Differential Evolution (DE), Gradient Evolution (GE) and Jumping Technique (+) named as Differential Gradient Evolution Plus (DGE+) is presented. The main concept of this hybrid algorithm is to enhance its exploration and exploitation ability. The proposed algorithm hybridizes the above-mentioned algorithms with the help of an improvised dynamic probability distribution, additionally provides a new shake off method to avoid premature convergence towards local minima. The performance of DGE+ is investigated in thirteen benchmark unconstraint functions and the results are compared to the other state-of-the-art meta-heuristics. The comparison shows that the proposed algorithm is able to outperform the other state-of-the-art meta-heuristics in almost all benchmark functions. To evaluate the efficiency of the DGE+ it has also been applied to complex constrained non-linear chemical design problems such as optimal operation of alkylation unit, reactor network design, optimal design of heat exchanger network, optimization of an isothermal continuous stirred tank reactor, the results of comparison revealed that the proposed algorithm is able to provide very compact, competitive and promising performance.

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